The data science and AI division at CSE is recruiting a PhD student in machine learning for a project on the efficient generalization using causality and auxiliary information.
Information about the project Machine learning is now an essential tool for scientists and engineers. It is used in diverse applications to predict outcomes from inputs by training models to minimize prediction error in training data. As widespread adoption reaches beyond research and the developers of such systems, the seams have started to show in this attractively simple idea. State-of-the-art models which achieve top accuracy on benchmark tasks fail to generalize to new examples and to highly related problem domains. In this project, we will study the combination of causal inference and learning using auxiliary information to improve the efficiency and domain robustness of learning algorithms.
Generalization in machine learning refers to a trained system performing well on previously unseen examples. These new examples are often assumed to follow the same distribution as training examples, which guarantees good generalization if the number of samples is large enough. In real-world applications, however, data often follows different patterns: 1) We often have access to different (auxiliary) information at training time than we do when the trained system is deployed, 2) The distribution of in-deployment samples often differs from those collected for training, 3) The number of samples is rarely as large as we would like it to be. In this project, we will develop sample-efficient learning algorithms which makes the best possible use of small numbers of training examples by exploiting auxiliary information and causal assumptions.
The position is placed in the research group led by Fredrik Johansson, currently comprised of 5 PhD students working on topics related to machine learning for improved decision making with applications in healthcare. The project is supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut & Alice Wallenberg Foundation.
Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden's largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of- systems.
The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish industry. Read more: https: // wasp-sweden.org/
The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more: https: // wasp-sweden.org/graduate-school/
Major responsibilities Your major responsibilities as a PhD student is to pursue your own doctoral studies. You will be enrolled in a graduate program in the Department of Computer Science and Engineering. You are expected to develop your own ideas and communicate scientific results orally as well as in written form. In addition, the position will include 20% departmental work, mostly teaching duties in Chalmers' undergraduate and masters-level courses or performing other duties corresponding to 20% of working hours.
Qualifications To qualify as a PhD student, you must have a master's-level degree, or a four-year bachelor's degree, corresponding to at least 240 higher education credits in a relevant field. The position requires sound verbal and written communication skills in Swedish and English. If Swedish is not your native language, you should be able to teach in Swedish after two years. Chalmers offers Swedish courses.
Contract terms Full-time temporary employment. The position is limited to a maximum of five years.
We offer Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg. Read more about working at Chalmers and our benefits for employees.
Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence. Equality and diversity are substantial foundations in all activities at Chalmers.
Application procedure The application should be marked with Ref 20220436 and written in English. The application should be sent electronically and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.
CV: (Please name the document: CV, Family name, Ref. number) • CV • Other, for example previous employments or leadership qualifications and positions of trust. • Two references that we can contact.
Personal letter: (Please name the document as: Personal letter, Family name, Ref. number) 1-3 pages where you: • Introduce yourself • Describe your previous experience of relevance for the position (e.g. education, thesis work and, if applicable, any other research activities) • Describe your future goals and future research focus
Other documents: • Copies of bachelor and/or master's thesis. • Attested copies and transcripts of completed education, grades and other certificates, e.g. TOEFL test results.
Use the button at the foot of the page to reach the application form.
Application deadline: 2nd October, 2022
For questions, please contact: Fredrik Johansson, CSE DSAI, firstname.lastname@example.org, +46 073 591 7101
Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position.
Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our six Areas of Advance; Energy, Health Engineering, Information and Communication Technology, Materials Science, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!